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      name:  <unnamed>
       log:  C:/Users/agerster/Dropbox/Projekt_Gebaeudeausweis/Auswertung JAERE_final/log/2019_6_5_analyses_transaction_offerprice.log
  log type:  text
 opened on:   5 Jun 2019, 14:36:14

. 
. 
. * number rof matched observations (not in last month)
. distinct obid $ifnotlastmonth & transaction == 0 

       |        Observations
       |      total   distinct
-------+----------------------
  obid |       1422       1422

. 
. *****************************************************
. ** Table 8 (Online Appendix B): Estimation Results on the Difference between logged Transaction and logged Asking Prices
. *****************************************************
. cap drop lkaufpreis_diff

. sort matchid notransaction

. bysort matchid (notransaction): gen lkaufpreis_diff = lkaufpreis - lkaufpreis[_n+1]   if _n==1  
(1,468 missing values generated)

. 
. reg lkaufpreis_diff i.postmai $ifnotlastmonth , vce(robust)

Linear regression                               Number of obs     =      1,422
                                                F(1, 1420)        =       0.81
                                                Prob > F          =     0.3673
                                                R-squared         =     0.0006
                                                Root MSE          =     .23935

------------------------------------------------------------------------------
             |               Robust
lkaufpreis~f |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.postmai |   .0113887   .0126272     0.90   0.367    -.0133813    .0361587
       _cons |  -.0664976    .008653    -7.68   0.000    -.0834717   -.0495234
------------------------------------------------------------------------------

. est sto interact

. 
. * only around cutoff (652 is May 2014)
. reg lkaufpreis_diff i.postmai if inrange(monat,`=652-3',`=651+3'), vce(cluster matchid)

Linear regression                               Number of obs     =        256
                                                F(1, 255)         =       0.04
                                                Prob > F          =     0.8373
                                                R-squared         =     0.0002
                                                Root MSE          =     .24501

                              (Std. Err. adjusted for 256 clusters in matchid)
------------------------------------------------------------------------------
             |               Robust
lkaufpreis~f |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.postmai |   .0063051   .0306651     0.21   0.837    -.0540839    .0666942
       _cons |  -.0416492   .0224217    -1.86   0.064    -.0858046    .0025061
------------------------------------------------------------------------------

. est sto interact_m3

. 
. *reg lkaufpreis_diff i.postmai if inrange(monat,651,652), vce(cluster matchid)
. reg lkaufpreis_diff i.postmai if inrange(monat,`=652-6',`=651+6'), vce(cluster matchid)

Linear regression                               Number of obs     =        530
                                                F(1, 529)         =       0.52
                                                Prob > F          =     0.4700
                                                R-squared         =     0.0009
                                                Root MSE          =     .24851

                              (Std. Err. adjusted for 530 clusters in matchid)
------------------------------------------------------------------------------
             |               Robust
lkaufpreis~f |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.postmai |  -.0151422   .0209456    -0.72   0.470    -.0562889    .0260046
       _cons |  -.0454924   .0112289    -4.05   0.000    -.0675511   -.0234336
------------------------------------------------------------------------------

. est sto interact_m6

. 
. *reg lkaufpreis_diff i.postmai if inrange(monat,651,652), vce(cluster matchid)
. reg lkaufpreis_diff i.postmai if inrange(monat,`=652-12',`=651+12'), vce(cluster matchid)

Linear regression                               Number of obs     =      1,086
                                                F(1, 1085)        =       0.13
                                                Prob > F          =     0.7159
                                                R-squared         =     0.0001
                                                Root MSE          =     .23274

                            (Std. Err. adjusted for 1,086 clusters in matchid)
------------------------------------------------------------------------------
             |               Robust
lkaufpreis~f |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.postmai |   .0051327   .0140976     0.36   0.716    -.0225289    .0327943
       _cons |  -.0630308   .0096204    -6.55   0.000    -.0819075   -.0441542
------------------------------------------------------------------------------

. est sto interact_m12

. 
. 
. *** tables for paper
. estout interact interact_m3 interact_m6 interact_m12, ///
>         cells(b(fmt(3) star) se(fmt(3)) /*ci(fmt(3))*/   ) ///
>         stats(N N_clust, fmt(%9.0fc %9.0fc)) ///
>         varwidth(12) starlevels(* 0.05 ** 0.01) ///
>         drop( ) style(tex) nobase

            &    interact  & interact_m3  & interact_m6  &interact_m12  \\
            &        b/se  &        b/se  &        b/se  &        b/se  \\
1.postmai   &       0.011  &       0.006  &      -0.015  &       0.005  \\
            &       0.013  &       0.031  &       0.021  &       0.014  \\
_cons       &      -0.066**&      -0.042  &      -0.045**&      -0.063**\\
            &       0.009  &       0.022  &       0.011  &       0.010  \\
N           &       1,422  &         256  &         530  &       1,086  \\
N_clust     &              &         256  &         530  &       1,086  \\

.         
. log close
      name:  <unnamed>
       log:  C:/Users/agerster/Dropbox/Projekt_Gebaeudeausweis/Auswertung JAERE_final/log/2019_6_5_analyses_transaction_offerprice.log
  log type:  text
 closed on:   5 Jun 2019, 14:36:15
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